Considerations for the Return of Genomic Results @HeidiRehm Heidi L. - - PowerPoint PPT Presentation

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Considerations for the Return of Genomic Results @HeidiRehm Heidi L. - - PowerPoint PPT Presentation

Considerations for the Return of Genomic Results @HeidiRehm Heidi L. Rehm, PhD, FACMG Medical Director, Broad Institute Clinical Research Sequencing Platform Associate Professor of Pathology, Brigham and Womens Hospital and Harvard Medical


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Considerations for the Return of Genomic Results

Heidi L. Rehm, PhD, FACMG

Medical Director, Broad Institute Clinical Research Sequencing Platform Associate Professor of Pathology, Brigham and Women’s Hospital and Harvard Medical School

@HeidiRehm

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Challenges to scaling genomic interpretation and ROR

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Technical validity and sample identity

▫ Orthogonal confirmation with original sample addresses issues that happen even with CLIA NGS  Analytical validity of results

▫ SNVs challenging in homologous regions ▫ InDels often challenging

 Sample mix‐ups during testing process ▫ Yet, duplicate specimens and orthogonal confirmation are not scalable

Consider making some data available separately as unconfirmed research results requiring CLIA confirmation

(e.g. PMS2, SMN1/2, VWF, STRC)

Courtesy: Diana Mandelker and Birgit Funke

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Quality Scores for NGS Data – When is Sanger required?

Require Sanger Assume TP Assume FP

Whole Genome Variants 373 Assume True Positive 31 Require Sanger (7.4%) 13 Assume False Positive 417 Total

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Novel null, 34% Reported null, 27% Reported missense, 39% ~5 million variants Technical exclusions

HGMD

*

<5% <1%

Gene exclusions Variant exclusions ~100‐200 variants ~10 variants for manual review

MedSeq Variant Analysis Pipeline and Detection Rates

Medical exome Novel LOF ClinVar *In non‐diagnostic testing, 92% of variants reported as pathogenic in HGMD had insufficient evidence to support the claim.

~5000 genes

~2% (0‐7) of filtered variants reported in MedSeq Several hours of review per genome Pathogenic Likely Pathogenic VUS – Favor Pathogenic Variant Type Average Review Time Variant with literature 90 min Variant with no literature 26 min

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Interpretation Differences in ClinVar

26% (97,422/377,075) of variants have ≥2 submitters in ClinVar 17% (16,631/97,422) are interpreted differently

NEJM May 27th, 2015

3.6% medically significant (P/LP vs VUS/LB/B) 1.7% medically significant among clinical lab submissions 11% (12,895/118,169) of variants have ≥2 submitters in ClinVar 17% (2229/12,895) are interpreted differently

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Pre‐

Discrepancy Resolution Process

Post‐

Discrepancy Resolution Process

87% resolution (211/242)

Harrison et al. Genet Med, in press Steven Harrison

Ambry Chicago GeneDx LMM

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~4% of cases per year received medium or high alerts

Genet Med. Apr 2012 PMID: 22481129

MedSeq Genome Reanalysis

22% (22/100) Participants Received New or Reclassified Variants Both, 3 Reclassified Finding(s), 10 Previously Unreported Finding(s), 9

Variant Knowledge Evolution

Expert Panel interpretations sometimes change as well

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Variant Reclassification Over 12 Years at the Laboratory for Molecular Medicine

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Variant Reclassification Over 12 Years at the Laboratory for Molecular Medicine

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Laboratory management of knowledge updates

1.Issue amended reports 2.Allow direct access to laboratory database (e.g. Emory) 3.Regularly deposit variants into ClinVar 4.Deliver automated knowledge updates on reported variants (e.g. GeneInsight)

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Reports, Structured Variant Data and Variant Updates Returned Via EHR (GeneInsight Clinic)

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Updated Variant Information

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Prototype of a proposed EHR App Will bring in 3‐4 star variants from ClinVar

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Proposal for AoU Genetic ROR

  • Begin with a small set of results that reach consensus for utility and sufficient evidence
  • Label “clinical” and expand scope once a successful process is achieved

▫ ACMG59 as starting point ▫ Pathogenic as starting point

  • Consider approaches to share additional data – label as “research”

▫ Enable participants to share their raw data broadly  Array genotypes, BAMs, VCFs  List of annotated novel, rare or suspicious variants ▫ Allow access to data when clinical context raises the prior probability of disease  CLIA confirmations and interpretations can be ordered as needed ▫ Enable other studies that can delve deeper into the significance of these variants

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Approaches to scale genomic interpretation

  • For novel predicted null variants, checklist can largely be automated if

gene and exon level curation is performed in advance

 Are null variants an established mechanism of disease?  How frequently are predicted null variants found in the gene in large population databases? Het vs hom? What is the constraint score in ExAC?  Are there other known pathogenic variants in the exon? Also check ExAC for nulls in that exon.  Is nonsense‐mediated decay predicted?  Are there predicted null variants reported 3' (and 5’) to the variant?  Is the exon alternatively spliced?

  • Rely on ClinVar review levels for reported variants

▫ Consider reporting only 3 star or 4 star variants ▫ Could add 2 star variants (all submitters agree)

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Hereditary Cancer Cardiovascular Disease Inborn Errors of Metabolism Neuro developmental Hearing Loss RASopathies EP RASopathies EP Other CDH1 EP PTEN EP TP53 EP Cardiomyopathy Cardiomyopathy EP KCNQ1 EP FH EP PAH EP Mito EP Brain Malformations EP Hearing Loss EP Application approved by ClinGen for 3 star submissions to ClinVar Planning to apply to ClinGen for 3 star submission level MODY EP ENIGMA EP CFTR EP CFTR EP InSiGHT EP PharmGKB PharmGKB

Variant Curation Expert Panels (ClinGen‐approved and in planning)

FAO EP Rett/Angelman‐ like Disorders

9318 expert reviewed variants in ClinVar (2.5%)

Somatic & Germline Cancer Curation Group Aminoacid‐

  • pathy EP
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Which 1‐2 star variants to report?

  • Not all 2 star variants are created equal
  • Not all 1 star variants are created equal
  • 2 star: How many labs agree? Only 2 or many?
  • Which groups(s) reported?

▫ Single submitter criteria provided (1 star) ▫ Experienced clinical lab  subjective – opinion of physicians and clinical lab peers  objective measures – volume of submissions in a disease area (data from ClinVar Miner)

  • Date of last evaluation (evaluated within last 1‐2 years)

50000 100000 150000 200000 250000 0 star 1 star w/ conflict 1 star single submitter 2 star 3/4 star

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hu025CEA (Heidi Rehm) ‐ GET‐Evidence variant report– PGP Project

http://evidence.pgp‐hms.org/genomes

Genome report

Variant Clinical Importance Impact Allele freq Summary

APOE‐C130R

High Well‐established pathogenic 14% This is generally known as the ApoE4 allele of ApoE and is associated with increased risk of Alzheimer's. 20‐25% of individuals are heterozygous for this variant, and 1‐2% are homozygous. Data from Khachaturian et al. suggests an average 7% of all individuals developed Alzheimer's by the age of 80; when this is split by ApoE4 status: 10% of ApoE4 heterozygotes (3% increased attributable risk), 40% of ApoE4 homozygotes (33% increased attributable risk), and 5% of non‐carriers (2% decreased attributable risk). Notably, their model suggests 70‐75% of people would eventually develop Alzheimer's by the age of 100 regardless of ApoE4 genotype (and 25‐30% are resistant, regardless of genotype), but that ApoE4 variants shift the disease onset to occur significantly earlier (4 years earlier for heterozygous carriers, 13 years for homozygotes). Complex/Other, Heterozygous

NOD2‐R702W

Low Likely pathogenic 3.30% NOD2 encodes a protein involved in bacterial recognition. This variant is associated with Crohn's disease in European populations, but not in Korean or Japanese groups. Complex/Other, Heterozygous

MBL2‐R52C

Low Likely pathogenic 4.90% This variant is associated with mannose binding protein deficiency which leads to impaired complement system immune response to mannose‐rich pathogens. Patients homozygous for this allele or compound heterozygous are likely to have increased susceptibility to infection, but Hellemann et al. report heterosis for intensive care outcomes in heterozygous subjects. The wild‐type version of this gene is known as variant allele A, while this is called variant allele D. See G54D (variant B) and G57E (variant C). Recessive, Carrier (Heterozygous)

APOA5‐S19W

Low Likely pathogenic 6.50% This variant, also known as APOA5*3, is associated with higher plasma triglyceride concentrations but no significant correlation with coronary artery disease itself has been found. Unknown, Heterozygous

MTRR‐I49M

Low Likely pathogenic 45% This common variant (HapMap allele frequency of 31.3%) in a protein involved in folate (B9) and cobalamin (B12) metabolism and is often reported as "MTRR I22M" (an alternative transcript position). Mothers homozygous for this variant are associated with having around a increased chance of a child with Down syndrome (risk of 0.4%, average risk in population is 0.25%). Notably, age plays a far larger role in the rate of Down syndrome (risk is 4.5% for a mother 45‐years‐of‐age), and it is unknown how this variant may combine with the effect of age. There are conflicting reports associating this variant with incidence of neural tube defects, possibly when combined with MTHFR A222V. Recessive, Carrier (Heterozygous)

CD40LG‐G219R

Low Uncertain pathogenic 1.10% Study of a single family with X‐linked immunodeficiency implicated this variant as causal when combined with XIAP‐G466X. The authors' hypothesis is that either variant alone has much less effect, if

  • any. Because 2% of males carry this variant, it is very unlikely that the variant alone has any severe effect.

Recessive, Carrier (Heterozygous)

Insufficiently evaluated variants (3319 variants)

Variant Prioritization score Allele freq Num of articles Zygosity and Prioritization Score Reasons

MC2R‐S74I

5 0.02%

  • Heterozygous. In OMIM, Polyphen 2: 0.995 (probably damaging), Testable gene in GeneTests

NEFL‐S472Shift

4 ?

  • Homozygous. Frameshift, Testable gene in GeneTests with associated GeneReview

RSPH4A‐W607Shift

4 ?

  • Heterozygous. Frameshift, Testable gene in GeneTests with associated GeneReview

TTN‐E190Shift

4 0.86%

  • Heterozygous. Frameshift, Testable gene in GeneTests with associated GeneReview

XDH‐R1296W

4 1.30%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.954 (probably damaging), Testable gene in GeneTests

CEP290‐E277Q

4 1.40%

  • Heterozygous. Polyphen 2: 0.956 (probably damaging), Testable gene in GeneTests with associated GeneReview

DPYD‐S534N

4 1.60% 2 Carrier (Heterozygous). Has unevaluated web hits, Polyphen 2: 0.996 (probably damaging), Testable gene in GeneTests

CEP290‐K838E

4 3.20%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: Unknown, Testable gene in GeneTests with associated GeneReview

LAMC2‐D247E

4 3.40% 1

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.328 (possibly damaging), Testable gene in GeneTests with associated GeneReview

F5‐P1404S

4 3.70%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: Unknown, Testable gene in GeneTests with associated GeneReview

COL11A2‐P1316T

4 4.60%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: Unknown, Testable gene in GeneTests with associated GeneReview

IL23R‐R381Q

4 4.80% 3

  • Heterozygous. In OMIM, In HuGENet GWAS, In PharmGKB, Polyphen 2: 0.997 (probably damaging)

ATP8B1‐R952Q

4 8.30%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.999 (probably damaging), Testable gene in GeneTests with associated GeneReview

RDH12‐R161Q

4 12%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.941 (probably damaging), Testable gene in GeneTests with associated GeneReview

SPG7‐R688Q

4 14% 3 Carrier (Heterozygous). In PharmGKB, Polyphen 2: 0.203 (possibly damaging), Testable gene in GeneTests with associated GeneReview

SPG7‐T503A

4 14% 1

  • Heterozygous. In PharmGKB, Polyphen 2: 0.001 (benign), Testable gene in GeneTests with associated GeneReview

DLL3‐F172C

4 15%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.981 (probably damaging), Testable gene in GeneTests with associated GeneReview

MSH6‐G39E

4 18% 3

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.873 (probably damaging), Testable gene in GeneTests with associated GeneReview

ATP7A‐V767L

4 25% 1

  • Heterozygous. In PharmGKB, Polyphen 2: Unknown, Testable gene in GeneTests with associated GeneReview

GPR98‐Y2232C

4 32%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.989 (probably damaging), Testable gene in GeneTests with associated GeneReview

NHLRC1‐P111L

4 34%

  • Heterozygous. Has unevaluated web hits, Polyphen 2: 0.992 (probably damaging), Testable gene in GeneTests with associated GeneReview

Variant 56 of 3319: MYH7‐R1500W

3 ?

  • Heterozygous. Polyphen 2: Unknown, Testable gene in GeneTests with associated GeneReview

Case Source Year Dx Age Dx Segregatio n Clinical hx; Family 1 Karkkainen 2004 DCM 55 yr not tested mother heart failure/car several family members d 2 Jerosch‐Herold 2008 DCM 56 yr 2 mother symptoms at 95 ( consistent with DCM) and 73 of HF) and 63 yr (dysp 3 Merlo 2013 DCM ? ? 4 Hazebroek 2015 DCM ? (>18 yr) ? 5 LMM 2013 DCM/LVNC 32 yr no fam hx past hx of IV drug use; eje improved 6 GeneDx 20?? DCM <13 yr homozygous 7 GeneDx 20?? DCM 8 GeneDx 20?? DCM 9 Invitae 2015 DCM/LVNC 34 yr Hispanic no fam hx peripartum cardiomyopa hypothyroidism; heart ha thyroid treatment but sti list 10 Geisinger 2016

Technical artifact

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Supporting Participants with a Genomic Result & Their Clinicians – Principles & Implications for All of Us

  • W. Andrew Faucett, MS, LGC

Director of Policy & Education Geisinger Health System wafaucett@geisinger.edu

@andyfaucett

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  • “focus not just on disease, but also on ways to

increase an individual’s chances of remaining healthy throughout life”

  • “empower study participants with data and

information to improve their own health”

Relevant All of Us guiding principles

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  • Participant focus groups:
  • Wanted Geisinger to guide project
  • Comfortable receiving ALL results
  • Accepted we do not understand some results
  • Importance of placing genomic results in EHR
  • Share results with participants
  • Education, medical support to patients &

clinicians

Geisinger MyCode Participant Driven Principles

Faucett WA & Davis FD, 2016, Appl Trans Genom

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  • Patient focus groups
  • Ethics Advisory Council (EAC)
  • Clinical Oversight Committee (COC)
  • Precision Health Patient Advisory Board

Engagement to Develop Return Process

Faucett WA & Davis FD, 2016, Appl Trans Genom

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  • 1. Geisinger expert consensus on which genes to

evaluate & return

  • 2. Pathogenic/likely pathogenic variants in medically

actionable genes

  • 3. Minimize false positives (specificity > sensitivity)
  • 4. Patients choose how to follow up clinically
  • 5. Supportive infrastructure for patients & clinicians

Principles of MyCode Genomic Results Program

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  • 1. Primary care clinician notified of result via EHR
  • 2. Patients notified in writing that result is available
  • 3. Clinical Genomics team calls patients

1. Disclose nature of results 2. Schedule follow‐up (detailed disclosure, clinical eval) 3. Encourage family communication of results

  • 4. Patients choose clinical follow‐up approach
  • 5. All patients receive educational/supportive materials
  • n relevant genetic condition
  • 6. Care coordination with co‐managing clinicians

Result return process

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Patient Support

  • Multiple service delivery models
  • Genetic counselors available for

phone consults 5 days/ week

  • Genetic counselors & physician geneticists

available for in‐person consults 3 days/week

  • Genetic Counselor for most results
  • Triage conditions with syndromic

features to geneticists

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Lessons – MyCode Patient Support

Follow‐up Status Positive Results % Clinical Genomics 245 45% PCP or specialist 73 13% Declined immediate follow‐up 134 25% Lost to follow‐up 38 7% Deceased/Withdrawn 9 2% In Process 45 8% Total 544 100%

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Results Returned

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  • Patient support
  • Opportunity to meet with clinical genomics team
  • Family history intake
  • Condition‐specific multi‐disciplinary clinics
  • Clinician support
  • EHR tools for detailed phenotyping, documentation
  • Continuing Medical Education
  • Opportunity to consult clinical genomics team
  • Both
  • Provider / Patient friendly genomic reports

Support in MyCode Genomic Results Program

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Lessons – MyCode Patient Support

  • Positive feedback from qualitative interviews
  • “[I]t’s a good thing to know for you and your family

members…if you find something you can nip in the bud, it’s not nearly as expensive”

  • “Nobody’s been very upset or even my kids who have

potential of having it themselves have been very laid back about it actually”

  • Facilitating cascade testing is challenging
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MyCode Clinician Support

  • CME modules
  • Low uptake, but want to know they are there
  • PCPs prefer brief, risk management focused on

support

  • PCPs prefer Genomics disclose results & guide

evaluation

  • PCP role is to support process
  • Want Genomics help with current management
  • Returning results increased clinician support of

MyCode

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Detailed discussion of results by genetics clinician Targeted discussion of results by ordering clinician

Per clinician & participant preferences Condition associated with increased risk of adverse psychological impact? Is patient a minor who had an adult‐onset condition identified?

No No Yes Yes

Disclosure of results via phone, patient portal, or written material

Per clinician & participant preferences

Pathogenic/Likely Pathogenic Variant Result

ClinGen Consent & Disclosure Recommendations Working Group

ACMG SFv2.0 gene recommendations completed

Disclosure of Results by ordering clinician (via phone

  • r in person);

priority referral

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33

All of Us - Thoughts On What To Return

  • ACMG 2.0 (59 genes)
  • Manageable numbers – 3.5 – 4%
  • “High Value” – medically actionable
  • GC community familiar
  • Commercial lab support – education

materials

  • Pharmacogenomics
  • Most participants will receive result (100%)
  • More value for older participants
  • Return with educational materials & limited

GC and pharmacist support

  • “Uninterpreted Data”
  • Process / Format
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34

V 3.0 ACMG 2.0 & PGX Uninterpreted Data V 2.0 ACMG 2.0 Pharmacogenomics V 1.0 ACMG 2.0

All of Us Results Sharing Versions

Confirm interest with each version

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  • David H. Ledbetter, Ph.D., FACMG
  • Huntingon Willard, Ph.D.
  • W. Andrew Faucett, MS, LGC
  • Christa L. Martin, Ph.D., FACMG
  • Marc Williams, MD, FACMG
  • Adam Buchanan, MS, MPH, LGC
  • Amy Sturm, MS, LGC
  • Michael Murray, MD, FACMG
  • Karen Wain, MS, LGC
  • Brenda Finucane, LGC
  • Marci Schwartz, MS, LGC
  • Miranda Hallquist, MSc, LGC
  • Janet Williams, MS, LGC
  • Heather Rocha, MS, LGC
  • Cara McCormick, MPH
  • Loren Gorgol, MS
  • Amanda Lazzeri, BS
  • Lauren Frisbie, BS
  • Carroll Flansburg, MA, MPH
  • David C. Carey, Ph.D.
  • Dan Davis, Ph.D.
  • Jennifer Wagner, Ph.D., J.D.
  • Michelle Meyer, Ph.D., J.D.
  • Ally Haggerty, MBA
  • Joe Leader, BA
  • Ethics Advisory Council members
  • Clinical Oversight Committee members
  • Focus group participants
  • Precision Health Patient Advisory Board
  • GEISINGER PATIENTS
  • Regeneron Genetics Center
  • Aris Baras, M.D.
  • Rick Dewey, M.D.
  • Evan Maxwell, Ph.D.
  • John Overton, Ph.D.
  • Jeffrey Reid, Ph.D.
  • Alan Shuldiner, M.D.
  • George Yancoploulos, M.D., Ph.D.
  • Laboratory for Molecular Medicine
  • Matthew S. Lebo, Ph.D.
  • Christina Austin-Tse, Ph.D.
  • Heather M. Mason-Suares, Ph.D.
  • Heidi Rehm, Ph.D., FACMG

MyCode Genomics Team

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SLIDE 36
  • Kelly Ormond, MS, LGC
  • W. Andrew Faucett, MS, LGC
  • Miranda Hallquist, MSc, LGC
  • Kyle Brothers, MD
  • Adam Buchanan, MS, MPH, LGC
  • Curtis Coughlin II, MS, MBe, CGC
  • Erin Currey
  • Laura Hercher, MS, CGC
  • Louanne Hudgins, MD, FACMG
  • Seema Jamal, MSc, LCGC, CCGC
  • Dave Kaufman, PhD
  • Howard Levy, MD, PhD
  • Holly Peay, MS
  • Erin Ramos, PhD, MPH
  • Myra Roche, MS, CGC
  • Maureen Smith, MS, CGC
  • Melissa Stosic, MS, CGC
  • Wendy Uhlmann, MS, CGC
  • Karen Wain, MS, LGC

ClinGen Consent & Disclosure Recommendations WG